PLOG: Table-to-Logic Pretraining for Logical Table-to-Text Generation. (arXiv:2205.12697v1 [cs.CL])

Logical table-to-text generation is a task that involves generating logically
faithful sentences from tables, which requires models to derive logical level
facts from table records via logical inference. It raises a new challenge on
the logical-level content planning of table-to-text models. However, directly
learning the logical inference knowledge from table-text pairs is very
difficult for neural models because of the ambiguity of natural language and
the scarcity of parallel data. Hence even large-scale pre-trained language
models present low logical fidelity …

arxiv generation logic text text generation